WCSE 2017
ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.197

Research on Intelligent Control System of Scaffold Based On PLC

Zhen Chen, Jue Lu, Jian Song, Wei-ye Tian

Abstract— The attached self-lifting scaffold is a new emerging scaffold technology for high-rise buildings. Generally speaking, because of the partial load, the deviation of hoist itself and environmental factors, scaffold in the process of lifting will appear the asynchrony problem. Aiming at this problem, the paper puts forward a method of using fuzzy control thinking which can adjust multiple hoists speed at the same time, so it can make the scaffolding stay at the synchronous state. The system applies the sensor to measure the tension value of each lifting point. After it is processed by the fuzzy control, it can use its reasoning ability to get the frequency value which the hoist needs to adjust. Using the way of USS communication to send the frequency value acquired by the reasoning to each inverter, so that it can change the lifting speed of each hoist. At last, the load of each position tends to be the same. It has been used by simulation experiment and the engineering application, which can verify that the intelligent control system has better effect on synchronous control in the scaffold lifting process.

Index Terms— PLC, fuzzy control, scaffold, inverter, USS communication

Zhen Chen, Jue Lu, Jian Song, Wei-ye Tian
School of Information Engineering, Wuhan University of Technology, CHINA
Zhen Chen, Jian Song
Key Laboratory of Fiber Optic Sensing Technology and Information Processing (Wuhan University of Technology), Ministry of Education, CHINA

ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]


Cite: Zhen Chen, Jue Lu, Jian Song, Wei-ye Tian, "Research on Intelligent Control System of Scaffold Based On PLC," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1129-1133, Beijing, 25-27 June, 2017.